In an ordinary image sensing apparatus having a lens system and an image sensing element, there is a risk of such obstacles as, for example, shading of an image to be sensed due to a drop in marginal lumination caused by the lens system. To counteract this effect, the lens system is designed using multiple lenses, for example, to prevent the occurrence of such obstacles. However, such multi-lens lens systems are expensive, and moreover, in most cases are difficult to use in compact cameras and the like.
By contrast, where signal intake is carried out according to XY coordinates as with an instrument that uses a semiconductor image sensing element, for example, the image can be corrected by digital processing of the image signal. Consequently, conventionally, techniques of digitally correcting distortion due to image sensing with an inexpensive lens system, or of such lens shading as a drop in marginal lumination and color migration, are proposed. For example, in JP-A-2004-266750, a correction technique like the following is proposed: In general, it can be thought that the lens shading is a function of the distance from the lens system optical axis to correction pixels. Therefore, in order to correct lens shading, first, a distance d from the lens system optical axis to the pixel to be corrected is calculated using Pythagoras's theorem d=√{square root over (x2+y2)}. Then, a shading coefficient that is a function of the distance from the lens system optical axis to the pixel to be corrected is applied to each of the pixels to be corrected, thereby implementing the correction.
When applying this type of shading correction, usually noise caused by dark current and the like of the pixels is corrected first, so as not to over-correct the noise by shading correction.
In addition, in a white point detection process for the purpose of WB (white balance) correction as well, detection cannot be done correctly if noise is present, and therefor, usually, the pixel noise is corrected first.
As a result, a method that corrects noise by measuring the OB level and subtracting the OB level from the values of the pixels (hereinafter called “OB correction”) is taken as the usual method of correcting noise. With this method, in a monitor mode that continuously reads field images while sampling pixels from the image sensing element for confirming the subject and processes the image signal (an electronic viewfinder display mode; hereinafter referred to as “EVF display mode”), the OB level measurement results of the immediately preceding field image are used to correct the OB level difference of the current field image as shown in FIG. 13. In addition, in a “still image sensing mode (main image)” that reads all the pixels from the image sensing element in single shot or a continuous shot for recording an image or images and processes the image signals, first, the OB level is measured when the image signal is read from the image sensing element as shown in FIG. 13. Then, the image signal is temporarily held in memory, and the OB level is subtracted when the image signal is read from the memory.
However, when the image signal is temporarily held in the memory and then read again for OB correction in the still image sensing mode as described above, the interval to the next image sensing lengthens, leading to user stress and lost image-sensing opportunities as a result.